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3,172 results for “Publications”
Supplementary Data for "Sequencing the Pandemic: Rapid and High-Throughput Processing and Analysis of COVID-19 Clinical Samples for 21st Century Public Health"
<p>Supplementary material for F1000 methods manuscript. Includes raw sequencing metrics for two COVID sequencing methodologies, as well as a complete cost breakdown for each methodology.</p>
A web-based tool for automatically linking clinical trials to their publications - example calculation
<p><strong>Objective</strong>: Evidence synthesis teams, physicians, policy makers, and patients and their families all have an interest in following the outcomes of clinical trials and would benefit from being able to evaluate both the results posted in trial registries and in the publications that arise from them. Manual searching for publications arising from a given trial is a laborious and uncertain process. We sought to create a statistical model to automatically identify PubMed articles likely to report clinical outcome results from each registered trial in ClinicalTrials.gov.</p> <p><strong>Materials and Methods</strong>: A machine learning-based model was trained on pairs (publications linked to specific registered trials). Multiple features were constructed based on the degree of matching between the PubMed article metadata and specific fields of the trial registry, as well as matching with the set of publications already known to be linked to that trial.</p> <p><strong>Results</strong>: Evaluation of the model using NCT-linked articles as gold standard showed that they tend to be top ranked (median best rank = 1.0), and 91% of them are ranked in the top ten.</p> <p><strong>Discussion</strong>: Based on this model, we have created a free, public web based tool at http://arrowsmith.psych.uic.edu/cgi-bin/arrowsmith_uic/TrialPubLinking/trial_pub_link_start.cgi that, given any registered trial in ClinicalTrials.gov, presents a ranked list of the PubMed articles in order of estimated probability that they report clinical outcome data from that trial. The tool should greatly facilitate studies of trial outcome results and their relation to the original trial designs.</p>
Global indicators framework for socially responsible research and innovation (RRI): How to monitor public and researcher perspectives (Supplemental material)
<p>This data upload provides a detailed account of indicators that can be used to measure RRI progress around the world against the UNESCO Recommendation for Science and Scientific Researchers at the level of individual researchers and public opinion. This data upload provides supplemental material for an article in Open Research Europe entitled, 'Global indicators framework for socially responsible research and innovation (RRI): How to monitor public and researcher perspectives'.</p> <p>Abstract for main article:</p> <p>As calls for more socially responsible research and innovation (RRI) policies and practices grow more insistent, the need for high quality indicators that can be used to evaluate progress is becoming increasingly important. Given the global nature of science, such indicators need to be relevant to countries across all world regions. Moreover, the methodological quality of indicators is critical to provide a strong foundation for long-term comparative measurement of the impacts of different kinds of policy intervention. There is a practical challenge in this effort relating to the uneven mechanisms for data collection and analysis available in different countries. There is also a geopolitical challenge in gaining buy-in from countries with very different, and sometimes competing, agendas. Here, the 2017 UNESCO-led Recommendation on Science and Scientific Researchers is highlighted as an existing vehicle that can enable cooperation on globally comparative measurement of socially responsible research and innovation. In particular, the quadrennial monitoring of the implementation of this wide-ranging global policy instrument that has been ratified by 195 countries affords a unique opportunity to add value for these countries by linking RRI to the 2017 Recommendation while establishing benchmark indicators for RRI more generally. As a practical and methodological contribution to the global community of science and innovation policymakers, researchers and research and innovation stakeholders committed to socially responsible research, this report contains specific, detailed survey questions and response options focusing on the public opinion and individual researchers’ level of measurement. It provides details of sources of benchmark survey data that have readily available open data that can be used to benchmark the development of socially responsible research and innovation over time from the vantage points of the public and researchers around the world. The aim of this kind of indicators framework is to enable evidence-based practice in socially responsible research and innovation. Robust and practical RRI measurement on a global scale can reduce the risk that well-intentioned but ill-conceived RRI policy and practice interventions create undetected, unchecked, and unreformed negative impacts in practice.</p>
Public Attitudes Towards the European Space Agency
<p>The data inherent in this dataset were collected between 11 February 2020 to 1 March 2020 as part of a public survey of German residents. The survey looked into attitudes and (hypothetical) behaviours related to the European Space Agency and European space activities. Convenience sampling and snowball sampling were employed over email, messengers and social media.</p> <p>This is a multiple imputation dataset, including an imputation variable, a weighting variable, as well as composite variables where applicable.</p> <p>Additional files include a generic codebook for the dataset and a print version of the online survey for a rough overview of the survey design. The survey content in the latter is in German.</p>
Experimental data related to publication: "Dislocation Avalanches: Earthquakes on the MicronScale"
<p>Each .tar file corresponds to a single micropillar compression experiment. The nomenclature of the uploaded dia_<strong>{dia}</strong>_v_<strong>{v}</strong>_p_<strong>{p}</strong>.tar files is the following:</p> <ul> <li>{dia}: The diameter of the micropillar in µm</li> <li>{v}: The compression platen velocity in µm / s</li> <li>{p}: Unique identifier of the micropillar for a given diameter and compression platen velocity</li> </ul> <p>The tar files have the following content:</p> <ul> <li>A tar.gz file which contains the raw Acoustic Emission (AE) data in a compressed file format. Uncompressing it results in one or multiple wav files. In case of multiple ones the covered time range is included at the end of the file name like: 300to800 means the time interval from the compression experiment between 300 s and 800 s. The units of the AE measurement data is 0.1 mV and the sampling rate is 25 MHz.</li> <li>The raw data from the nanoindenter (time, force, displacement, etc.) is located in the file with .dat extension.</li> </ul>
The Data Set for the Publication "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer"
<p>In the scope of the ambitious EU goals of carbon neutrality in 2050, building energy efficiency is one of the crucial segments. To ensure a faster energy transition process, innovations are needed at various built environment-related sectors - starting from building components up to urban level energy management advancements.</p> <p>Phase change material (PCM) enriched building components allow to shift the existing paradigm - to make a switch from the static building components to dynamic ones able to take an active part in building energy balance by ensuring energy storage in the building thermal envelope.</p> <p>The data set presented here supports the paper "Laboratory Testing of Small Scale Solar Facade Module with Phase Change Material and Adjustable Insulation Layer". The design of the façade module, experimental setup, used equipment, the plan of the experiment, and obtained results are described in the paper. The provided data set provides heat-flux and average temperature (in PCM) measurements.</p>
Worldwide Gender Differences in Public Code Contributions - Replication Package
<p><strong>Worldwide Gender Differences in Public Code Contributions - Replication Package</strong></p> <p>This document describes how to replicate the findings of the paper: Davide Rossi and Stefano Zacchiroli, 2022, <em>Worldwide Gender Differences in Public Code Contributions</em>. In Software Engineering in Society (ICSE-SEIS'22), May 21-29, 2022, Pittsburgh, PA, USA. ACM, New York, NY, USA, 12 pages. <a href="https://doi.org/10.1145/3510458.3513011">https://doi.org/10.1145/3510458.3513011</a></p> <p>This document comes with the software needed to mine and analyze the data presented in the paper.</p> <p><strong>Prerequisites</strong></p> <p>These instructions assume the use of the <a href="https://www.gnu.org/software/bash/">bash</a> shell, the <a href="https://www.python.org/">Python</a> programming language, the <a href="https://www.postgresql.org/">PosgreSQL</a> DBMS (version 11 or later), the <a href="https://facebook.github.io/zstd/">zstd</a> compression utility and various usual *nix shell utilities (cat, pv, ...), all of which are available for multiple architectures and OSs.<br> It is advisable to create a <a href="https://docs.python.org/3/tutorial/venv.html">Python virtual environment</a> and install the following PyPI packages: <code>click==8.0.3 cycler==0.10.0 gender-guesser==0.4.0 kiwisolver==1.3.2 matplotlib==3.4.3 numpy==1.21.3 pandas==1.3.4 patsy==0.5.2 Pillow==8.4.0 pyparsing==2.4.7 python-dateutil==2.8.2 pytz==2021.3 scipy==1.7.1 six==1.16.0 statsmodels==0.13.0</code></p> <p><strong>Initial data</strong></p> <ul> <li><code>swh-replica</code>, a PostgreSQL database containing a copy of Software Heritage data. The schema for the database is available at <a href="https://forge.softwareheritage.org/source/swh-storage/browse/master/swh/storage/sql/">https://forge.softwareheritage.org/source/swh-storage/browse/master/swh/storage/sql/</a>.<br> We retrieved these data from <a href="https://www.softwareheritage.org">Software Heritage</a>, in collaboration with the archive operators, taking an archive snapshot as of 2021-07-07. We cannot make these data available in full as part of the replication package due to both its volume and the presence in it of personal information such as user email addresses. However, equivalent data (stripped of email addresses) can be obtained from the Software Heritage archive dataset, as documented in the article: Antoine Pietri, Diomidis Spinellis, Stefano Zacchiroli, <em>The Software Heritage Graph Dataset: Public software development under one roof</em>. In proceedings of MSR 2019: The 16th International Conference on Mining Software Repositories, May 2019, Montreal, Canada. Pages 138-142, IEEE 2019. <a href="http://dx.doi.org/10.1109/MSR.2019.00030">http://dx.doi.org/10.1109/MSR.2019.00030</a>.<br> Once retrieved, the data can be loaded in PostgreSQL to populate <code>swh-replica</code>.</li> <li><code>names.tab</code> - forenames and surnames per country with their frequency</li> <li><code>zones.acc.tab</code> - countries/territories, timezones, population and world zones</li> <li><code>c_c.tab</code> - ccTDL entities - world zones matches</li> </ul> <p><strong>Data preparation</strong></p> <ul> <li>Export data from the <code>swh-replica</code> database to create <code>commits.csv.zst</code> and <code>authors.csv.zst</code> <code>sh> ./export.sh</code></li> <li>Run the authors cleanup script to create <code>authors--clean.csv.zst</code> <code>sh> ./cleanup.sh authors.csv.zst</code></li> <li>Filter out implausible names and create <code>authors--plausible.csv.zst</code> <code>sh> pv authors--clean.csv.zst | unzstd | ./filter_names.py 2> authors--plausible.csv.log | zstdmt > authors--plausible.csv.zst</code></li> </ul> <p><strong>Gender detection</strong></p> <ul> <li>Run the gender guessing script to create <code>author-fullnames-gender.csv.zst</code> <code>sh> pv authors--plausible.csv.zst | unzstd | ./guess_gender.py --fullname --field 2 | zstdmt > author-fullnames-gender.csv.zst</code></li> </ul> <p><strong>Database creation and data ingestion</strong></p> <ul> <li> <p>Create the PostgreSQL DB <code>sh> createdb gender-commit </code>Notice that from now on when prepending the <code>psql></code> prompt we assume the execution of psql on the <code>gender-commit</code> database.</p> </li> <li> <p>Import data into PostgreSQL DB <code>sh> ./import_data.sh</code></p> </li> </ul> <p><strong>Zone detection</strong></p> <ul> <li>Extract commits data from the DB and create <code>commits.tab</code>, that is used as input for the gender detection script<br> <code>sh> psql -f extract_commits.sql gender-commit</code></li> <li>Run the world zone detection script to create <code>commit_zones.tab.zst</code> <code>sh> pv commits.tab | ./assign_world_zone.py -a -n names.tab -p zones.acc.tab -x -w 8 | zstdmt > commit_zones.tab.zst </code>Use <code>./assign_world_zone.py --help</code> if you are interested in changing the script parameters.</li> <li>Read zones assignment data from the file into the DB<br> <code>psql> \copy commit_culture from program 'zstdcat commit_zones.tab.zst | cut -f1,6 | grep -Ev ''\s$'''</code></li> </ul> <p><strong>Extraction and graphs</strong></p> <ul> <li>Run the script to execute the queries to extract the data to plot from the DB. This creates <code>commits_tz.tab</code>, <code>authors_tz.tab</code>, <code>commits_zones.tab</code>, <code>authors_zones.tab</code>, and <code>authors_zones_1620.tab</code>.<br> Edit <code>extract_data.sql</code> if you whish to modify extraction parameters (start/end year, sampling, ...). <code>sh> ./extract_data.sh</code></li> <li>Run the script to create the graphs from all the previously extracted tabfiles. This will generate <code>commits_tzs.pdf</code>, <code>authors_tzs.pdf</code>, <code>commits_zones.pdf</code>, <code>authors_zones.pdf</code>, and <code>authors_zones_1620.pdf</code>. <code>sh> ./create_charts.sh</code></li> </ul> <p><strong>Additional graphs</strong></p> <p>This package also includes some already-made graphs</p> <ul> <li><code>authors_zones_1.pdf</code>: stacked graphs showing the ratio of female authors per world zone through the years, considering all authors with at least one commit per period</li> <li><code>authors_zones_2.pdf</code>: ditto with at least two commits per period</li> <li><code>authors_zones_10.pdf</code>: ditto with at least ten commits per period</li> </ul>
Data to support the publication "The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment" https://doi.org/10.3390/land10090964
<p>Underlying data of soil measurements and analysis by TUC team for the publication “The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment” <a href="https://doi.org/10.3390/land10090964">https://doi.org/10.3390/land10090964</a> from the SoilCare project study sites in Crete. </p> <p>Abstract:</p> <p>The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management–or with some omissions–, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.</p>
Supporting publication for 'Prevalence sample-based guidance for reporting 2021 data'
<p>The record is aimed at helping the reporting countries to submit their sample-based level data to the EFSA Data Collection Framework. We include here two excel files and one XML file, and we give below specific information on their use.</p> <p>The two Excel documents help in mapping terms from the matrix catalogue ZOO_CAT_MATRIX used in the aggregated prevalence data model to FoodEx2 codes, and offer examples on how prevalence data can be reported using SSD2 and how data are aggregated afterwards. The XML file is the same example as in the Excel file with similar title but in the XML format that allows for it be uploaded in the Data Collection Framework.</p>
Data for the publication "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM"
<p>These data are a set of 1yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments of precipitation (i.e., diagnostic and prognostic). The outputs include diagnostics from the satellite simulator COSP2.<br> The data are used in the manuscript entitled "Too frequent and too light Arctic snowfall with incorrect precipitation phase partitioning in the MIROC6 GCM". All data used in this study are available from the corresponding author upon request.</p>
Landfill: An open dataset of code smells with public evaluation
<p>Code smells are symptoms of poor design and implementation choices that may hinder code comprehension and possibly increase the change- and fault-proneness of source code. Several techniques have been proposed in the literature for detecting code smells. These techniques are generally evaluated by comparing their accuracy on a set of detected candidate code smells against a manually-produced oracle. Unfortunately, such comprehensive sets of annotated code smells are not available in the literature, with only a few exceptions. This dataset provides 243 instances of five types of code smells identified from 20 open-source software projects. In particular, it contains a SQL file with the information concerning such instances and a zip file with their source code.</p>
Data set for publication: Extended SINDICOMP: Characterizing MV Voltage Transformers with Sine Waves
<p>This is dataset for paper published:</p> <p>Crotti, G.; D’Avanzo, G.; Giordano, D.; Letizia, P.S.; Luiso, M. Extended SINDICOMP: Characterizing MV Voltage Transformers with Sine Waves. <em>Energies</em> <strong>2021</strong>, <em>14</em>, 1715. https://doi.org/10.3390/en14061715</p> <p> </p> <p>Excel file provides data for Table 2, Table 4 and Figure 10 a.</p>
Dataset for publication "Measuring Harmonics With Inductive Voltage Transformers in Presence of Subharmonics"
<p>This is a dataset for paper published:</p> <p>G. Crotti, G. D’Avanzo, P. S. Letizia and M. Luiso, "Measuring Harmonics With Inductive Voltage Transformers in Presence of Subharmonics," in <em>IEEE Transactions on Instrumentation and Measurement</em>, vol. 70, pp. 1-13, 2021, Art no. 9005013, doi: 10.1109/TIM.2021.3111995.</p> <p> </p> <p>Excel file provides data for Figures from 9 to 16.</p>
Data set for publication: A New Industry-Oriented Technique for the Wideband Characterization of Voltage Transformers
<p>This is dataset for paper published:</p> <p>G. Crotti, D. Giordano, G. D'Avanzo, P.S. Letizia, M. Luiso, "A New Industry-Oriented Technique for the Wideband Characterization of Voltage Transformers", Measurement, Volume 182, 2021, 109674, ISSN 0263-2241,<br> https://doi.org/10.1016/j.measurement.2021.109674.</p> <p> </p> <p>Excel file provides data for Figure 3, 4, 6 and 7.</p>
Topical Classification of Food Safety Publications with a Knowledge Base – materials
<p>Supplementary material for the article titled "<strong><a href="https://doi.org/10.1007/978-981-19-4364-5_48">Topical Classification of Food Safety Publications with a Knowledge Base</a></strong>".</p> <p><strong>Citation</strong></p> <p>If you use this data in research work, please cite this paper:</p> <p>Sowinski, P., Wasielewska-Michniewska, K., Ganzha, M., & Paprzycki, M. (2022). Topical Classification of Food Safety Publications with a Knowledge Base. In <em>Sustainable Technology and Advanced Computing in Electrical Engineering</em> (pp. 673-693). Springer, Singapore.</p> <p>BibTeX:</p> <pre><code>@incollection{sowinski2022topical, title={Topical Classification of Food Safety Publications with a Knowledge Base}, author={Sowinski, Piotr and Wasielewska-Michniewska, Katarzyna and Ganzha, Maria and Paprzycki, Marcin}, booktitle={Sustainable Technology and Advanced Computing in Electrical Engineering}, pages={673--693}, year={2022}, publisher={Springer}, doi={10.1007/978-981-19-4364-5_48} }</code></pre> <p> </p>
Data and code for publication: A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging
<p>Data & Code release for publication:</p> <p>Rebecca Buchholz, Sebastian Krossa, Maria K Andersen, Michael Holtkamp, Michael Sperling, Uwe Karst, May-Britt Tessem, A simple preparation protocol for shipping and storage of tissue sections for laser ablation-inductively coupled plasma-mass spectrometry imaging, <em>Metallomics</em>, Volume 14, Issue 3, March 2022, mfac013, <a href="https://doi.org/10.1093/mtomcs/mfac013">https://doi.org/10.1093/mtomcs/mfac013</a></p> <p>Python code for LA ICP MS imaging data segmentation</p> <p>Code & Data also on <a href="https://github.com/sekro/la-icp-msi_segmentation">github</a></p> <p>Thresholding based segmentation of LA-ICP-MS imaging data</p> <p>Description</p> <p><a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/main.py">src/main.py</a> - run this to process LA ICP MS data in data folder - generates matplotlib.figures - project specific setup <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/laicpms_data_handler.py">src/laicpms_data_handler.py</a> - contains object to import, handle and segment (shimadzu) raw data</p> <p>Dependencies</p> <p>Python 3.8.1 or newer</p> <p>For packages see <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/requirements.txt">requirements.txt</a></p> <p>Data</p> <p>LA-ICP-MS imaging data of human prostate tissue of the elements Zn, Fe & P. Details on data generation & collection in <a href="https://doi.org/10.1093/mtomcs/mfac013">publication</a>. LA-ICP-MS imaging data as plain text files (comma-separated values)</p> <ul> <li>Condition 1 = fresh frozen (FF)</li> <li>Condition 2 = room temperature vacuum dried and sealed (RTV)</li> <li>Condition 3 = formalin fixed (FFix)</li> <li>Condition 4 = formalin fixed, paraffin sealed (FFPS)</li> </ul> <p>3 replicate sectioning sets named A, B, C</p> <p>File-naming: LA_Data_CISN1.csv, where I = [1, 2, 3, 4] is indicating the condition used and N = [A, B, C] is indicating the replicate set</p> <p>License</p> <p>Data</p> <p>CC-BY 4.0 - respective <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/data/LICENSE">LICENSE</a> file in data folder</p> <p>Source code</p> <p>MIT - respective <a href="https://github.com/sekro/la-icp-msi_segmentation/blob/master/src/LICENSE">LICENSE</a> file in src folder</p>
Data for the publication "Assessing the potential for simplification in global climate model cloud microphysics"
<p>This repository contains the data for the paper:</p> <p>Authors: Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann<br> Titel: Assessing the potential for simplification in global climate model cloud microphysics<br> Date: 2022</p> <p>Note that the scripts can be found in the accompanying package (https://doi.org/10.5281/zenodo.5506588)</p>
An annotated corpus of clinical trial publications supporting schema-based relational information extraction
<p>Repository of an annotated corpus of clinical trial abstracts supporting schema-based relational information extraction and the code for the inter-annotation agreement calculation and the baseline information extraction method.</p>
Source data to publication "Benchmarking of Analysis Strategies for Data-Independent Acquisition Proteomics Using a Large-Scale Dataset Comprising Inter-Patient Heterogeneity"
<p>Source data to publication "Benchmarking of Analysis Strategies for Data-Independent Acquisition Proteomics Using a Large-Scale Dataset Comprising Inter-Patient Heterogeneity".</p> <p>Data and further information at GitHub repository https://github.com/kreutz-lab/dia-benchmarking (DOI: 10.5281/zenodo.6371925)</p>
SCRIPTA. Site Caennais de Recherche Informatique et de Publication des Textes Anciens.
<p>SCRIPTA est une base de données des chartes normandes des Xe-XIIIe siècles. Il s’agit d’une base évolutive, non exhaustive, en cours d’enrichissement. Le corpus réunit des actes qui, pour la plupart, ont été auparavant édités dans des éditions anciennes dispersées ou qui ont été signalés dans d’autres bases de données. La base met à disposition les textes des actes et une analyse succincte, sans constituer une édition critique détaillée des documents. Les données analytiques sont les suivantes : degré d’authenticité, genre d'acte, type d'action juridique d'acte, lieu d'émission, auteur, fonction (et institution) de l’auteur, bénéficiaire de l’acte, sa fonction/institution, datation, tradition (liste des témoins, copies et éditions), bibliographie et analyse succincte (court résumé) de l'acte. Le texte des actes est donné dans sa langue originelle, sans traduction, sans notes critiques.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.